THE AUDITORY MODELING TOOLBOX

Applies to version: 1.6.0

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MCLACHLAN2021
A dynamic ideal-observer model of human sound localization

Usage:

[results,template,target] = mclachlan2014(template,target,'num_exp',20,'sig_S',4.2);

Input parameters:

template

struct with the fields

  • fs : sampling rate (Hz)
  • fc : ERB frequency channels (Hz)
  • itd0 : itd computed for each hrir (samples)
  • H : Matrix containing absolute values of HRTFS for all grid points
  • coords : Matrix containing cartesian coordinates of all grid points, normed to radius 1m
  • T : angular template for each coordinate
target

struct with the fields

  • fs : sampling rate
  • fc : ERB frequency channels
  • itd0 : itd corresponding to source position
  • S : sound source spectrum
  • H : Matrix containing absolute values of HRTFS for all source directions
  • coords : Matrix containing cartesian coordinates of all source positions to be estimated, normed to radius 1m
  • T : angular template for each coordinate

Output parameters:

doa

directions of arrival in spherical coordinates

  • est : estimated [num_sources, num_repetitions, 3]
  • real : actual [num_sources, 3]
params

additional model's data computed for estimations

  • est_idx : Indices corresponding to template direction where the maximum probability density for each source position is found
  • est_loglik : Log-likelihood of each estimated direction
  • post_prob : Maximum posterior probability density for each target source
  • freq_channels : number of auditory channels
  • T_template : Struct with template data elaborated by the model
  • T_target : Struct with target data elaborated by the model

Description:

mclachlan2021(...) is a dynamic ideal-observer model of human sound localization, by which we mean a model that performs optimal information processing within a Bayesian context. The model considers all available spatial information contained within the acoustic signals encoded by each ear over a specified hear rotation. Parameters for the optimal Bayesian model are determined based on psychoacoustic discrimination experiments on interaural time difference and sound intensity.

MCLACHLAN2021 accepts the following optional parameters:

'num_exp',num_exp Set the number of localization trials. Default is num_exp = 500.
'SNR',SNR Set the signal to noise ratio corresponding to different sound source intensities. Default value is SNR = 75 [dB]
'dt',dt Time between each acoustic measurement in seconds. Default value is dt = 0.005.
'sig_itd0',sig Set standard deviation for the noise on the initial itd. Default value is sig_itd0 = 0.569.
'sig_itdi',sig Set standard deviation for the noise on the itd change per time step. Default value is sig_itdi = 1.
'sig_I',sig Set standard deviation for the internal noise. Default value is sig_I = 3.5.
'sig_S',sig Set standard deviation for the variation on the source spectrum. Default value is sig_S = 3.5.
'rot_type',type Set rotation type. Options are 'yaw', 'pitch' and 'roll'. Default value is 'yaw'.
'rot_size',size Set rotation amount in degrees. Default value is rot_size = 0.
'stim_dur',dur Set stimulus duration in seconds. Default value is stim_dur = 0.1.

Further, cache flags (see amt_cache) can be specified.

Requirements:

  1. SOFA API v1.1 or higher from http://sourceforge.net/projects/sofacoustics for Matlab (e.g. in thirdparty/SOFA)

References:

R. Barumerli, P. Majdak, R. Baumgartner, J. Reijniers, M. Geronazzo, and F. Avanzini. Predicting directional sound-localization of human listeners in both horizontal and vertical dimensions. In Audio Engineering Society Convention 148. Audio Engineering Society, 2020.

J. Reijniers, D. Vanderleist, C. Jin, C. S., and H. Peremans. An ideal-observer model of human sound localization. Biological Cybernetics, 108:169--181, 2014.

G. McLachlan, P. Majdak, J. Reijniers, and H. Peremans. Towards modelling active dynamic sound localisation based on Bayesian inference. Acta Acustica, 2021.